Load all required libraries.

library(tidyverse)
## Warning: package 'tidyverse' was built under R version 3.6.3
## -- Attaching packages ------------------------------------------------------------------------ tidyverse 1.3.0 --
## v ggplot2 3.3.2     v purrr   0.3.4
## v tibble  3.0.3     v dplyr   1.0.0
## v tidyr   1.1.0     v stringr 1.4.0
## v readr   1.3.1     v forcats 0.5.0
## Warning: package 'ggplot2' was built under R version 3.6.3
## Warning: package 'tibble' was built under R version 3.6.3
## Warning: package 'readr' was built under R version 3.6.3
## Warning: package 'dplyr' was built under R version 3.6.3
## Warning: package 'forcats' was built under R version 3.6.3
## -- Conflicts --------------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
library(plotly)
## Warning: package 'plotly' was built under R version 3.6.3
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
library(broom)
## Warning: package 'broom' was built under R version 3.6.3

Read in raw data from RDS.

raw_data <- readRDS("./n1_n2_cleaned_cases.rds")

Make a few small modifications to names and data for visualizations.

final_data <- raw_data %>% mutate(log_copy_per_L = log10(mean_copy_num_L)) %>%
  rename(Facility = wrf) %>%
  mutate(Facility = recode(Facility, 
                           "NO" = "WRF A",
                           "MI" = "WRF B",
                           "CC" = "WRF C"))

Seperate the data by gene target to ease layering in the final plot

#make three data layers
only_positives <<- subset(final_data, (!is.na(final_data$Facility)))
only_n1 <- subset(only_positives, target == "N1")
only_n2 <- subset(only_positives, target == "N2")
only_background <<-final_data %>% 
  select(c(date, cases_cum_clarke, new_cases_clarke, X7_day_ave_clarke, cases_per_100000_clarke)) %>%
  group_by(date) %>% summarise_if(is.numeric, mean)

#specify fun colors
background_color <- "#7570B3"
seven_day_ave_color <- "#E6AB02"
marker_colors <- c("N1" = '#1B9E77',"N2" ='#D95F02')
#remove facilty C for now
#only_n1 <- only_n1[!(only_n1$Facility == "WRF C"),]
#only_n2 <- only_n2[!(only_n2$Facility == "WRF C"),]

only_n1 <- only_n1[!(only_n1$Facility == "WRF A" & only_n1$date == "2020-11-02"), ]
only_n2 <- only_n2[!(only_n2$Facility == "WRF A" & only_n2$date == "2020-11-02"), ]

Build the main plot

      #first layer is the background epidemic curve
        p1 <- only_background %>%
              plotly::plot_ly() %>%
              plotly::add_trace(x = ~date, y = ~new_cases_clarke, 
                                type = "bar", 
                                hoverinfo = "text",
                                text = ~paste('</br> Date: ', date,
                                                     '</br> Daily Cases: ', new_cases_clarke),
                                alpha = 0.5,
                                name = "Daily Reported Cases",
                                color = background_color,
                                colors = background_color,
                                showlegend = FALSE) %>%
            layout(yaxis = list(title = "Clarke County Daily Cases", showline=TRUE)) %>%
            layout(legend = list(orientation = "h", x = 0.2, y = -0.3))
        
        #renders the main plot layer two as seven day moving average
        p1 <- p1 %>% plotly::add_trace(x = ~date, y = ~X7_day_ave_clarke, 
                             type = "scatter",
                             mode = "lines",
                             hoverinfo = "text",
                            text = ~paste('</br> Date: ', date,
                                                     '</br> Seven-Day Moving Average: ', X7_day_ave_clarke),
                             name = "Seven Day Moving Average Athens",
                             line = list(color = seven_day_ave_color),
                             showlegend = FALSE)
      

        
        #renders the main plot layer three as positive target hits
        
        p2 <- plotly::plot_ly() %>%
          plotly::add_trace(x = ~date, y = ~mean_copy_num_L,
                                       type = "scatter",
                                       mode = "markers",
                                       hoverinfo = "text",
                                       text = ~paste('</br> Date: ', date,
                                                     '</br> Facility: ', Facility,
                                                     '</br> Target: ', target,
                                                     '</br> Copies/L: ', round(mean_copy_num_L, digits = 2)),
                                       data = only_n1,
                                       symbol = ~Facility,
                                       marker = list(color = '#1B9E77', size = 8, opacity = 0.65),
                                       showlegend = FALSE) %>%
          plotly::add_trace(x = ~date, y = ~mean_copy_num_L,
                                       type = "scatter",
                                       mode = "markers",
                                       hoverinfo = "text",
                                       text = ~paste('</br> Date: ', date,
                                                     '</br> Facility: ', Facility,
                                                     '</br> Target: ', target,
                                                     '</br> Copies/L: ', round(mean_copy_num_L, digits = 2)),
                                       data = only_n2,
                                       symbol = ~Facility,
                                       marker = list(color = '#D95F02', size = 8, opacity = 0.65),
                                       showlegend = FALSE) %>%
            layout(yaxis = list(title = "SARS CoV-2 Copies/L", 
                                 showline = TRUE,
                                 type = "log",
                                 dtick = 1,
                                 automargin = TRUE)) %>%
            layout(legend = list(orientation = "h", x = 0.2, y = -0.3))
        
        #adds the limit of detection dashed line
        p2 <- p2 %>% plotly::add_segments(x = as.Date("2020-03-14"), 
                                          xend = ~max(date + 10), 
                                          y = 3571.429, yend = 3571.429,
                                          opacity = 0.35,
                                          line = list(color = "black", dash = "dash")) %>%
          layout(annotations = list(x = as.Date("2020-03-28"), y = 3.8, xref = "x", yref = "y", 
                                    text = "Limit of Detection", showarrow = FALSE))

        

        p1
## Warning: `arrange_()` is deprecated as of dplyr 0.7.0.
## Please use `arrange()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.
## Warning: Ignoring 1 observations
        p2
## Warning: `group_by_()` is deprecated as of dplyr 0.7.0.
## Please use `group_by()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.

Combine the two main plot pieces as a subplot

#seperate n1 and n2 frames by site
#n1
wrf_a_only_n1 <- subset(only_n1, Facility == "WRF A")
wrf_b_only_n1 <- subset(only_n1, Facility == "WRF B")
wrf_c_only_n1 <- subset(only_n1, Facility == "WRF C")

#n2
wrf_a_only_n2 <- subset(only_n2, Facility == "WRF A")
wrf_b_only_n2 <- subset(only_n2, Facility == "WRF B")
wrf_c_only_n2 <- subset(only_n2, Facility == "WRF C")


#rejoin the old data frames then seperate in to averages for each plant. 
wrfa_both <- full_join(wrf_a_only_n1, wrf_a_only_n2)%>%
  select(c(date, mean_total_copies)) %>%
  group_by(date) %>%
  summarize_if(is.numeric, mean) %>%
  ungroup() %>%
  mutate(log_total_copies_both = log10(mean_total_copies))
## Joining, by = c("date", "cases_cum_clarke", "new_cases_clarke", "X7_day_ave_clarke", "cases_per_100000_clarke", "Facility", "collection_num", "target", "mean_copy_num_uL_rxn", "mean_copy_num_L", "sd_L", "mean_total_copies", "sd_total_copies", "log_copy_per_L")
wrfb_both <- full_join(wrf_b_only_n1, wrf_b_only_n2)%>%
  select(c(date, mean_total_copies)) %>%
  group_by(date) %>%
  summarize_if(is.numeric, mean) %>%
  ungroup() %>%
  mutate(log_total_copies_both = log10(mean_total_copies))
## Joining, by = c("date", "cases_cum_clarke", "new_cases_clarke", "X7_day_ave_clarke", "cases_per_100000_clarke", "Facility", "collection_num", "target", "mean_copy_num_uL_rxn", "mean_copy_num_L", "sd_L", "mean_total_copies", "sd_total_copies", "log_copy_per_L")
wrfc_both <- full_join(wrf_c_only_n1, wrf_c_only_n2)%>%
  select(c(date, mean_total_copies)) %>%
  group_by(date) %>%
  summarize_if(is.numeric, mean) %>%
  ungroup() %>%
  mutate(log_total_copies_both = log10(mean_total_copies))
## Joining, by = c("date", "cases_cum_clarke", "new_cases_clarke", "X7_day_ave_clarke", "cases_per_100000_clarke", "Facility", "collection_num", "target", "mean_copy_num_uL_rxn", "mean_copy_num_L", "sd_L", "mean_total_copies", "sd_total_copies", "log_copy_per_L")
#get max date
maxdate <- max(wrfa_both$date)
mindate <- min(wrfa_both$date)

Build loess smoothing figures figures

This makes the individual plots

#**************************************WRF A PLOT**********************************************
#add trendlines 
#extract data from geom_smooth
#both extract
# *********************************span 0.6***********************************
#*****************Must always update the n = TOTAL NUMBER OF DAYS*************************
extract_botha <- ggplot(wrfa_both, aes(x = date, y = log_total_copies_both)) + 
  stat_smooth(aes(outfit=fit_botha<<-..y..), method = "loess", color = '#1B9E77', 
              span = 0.6, n = 177)
## Warning: Ignoring unknown aesthetics: outfit
#look at the fits to align dates and total observations
#both
extract_botha
## `geom_smooth()` using formula 'y ~ x'

fit_botha
##   [1] 11.56837 11.63422 11.69958 11.76402 11.82714 11.88852 11.94775 12.00442
##   [9] 12.05899 12.11223 12.16418 12.21484 12.26426 12.31245 12.35944 12.40525
##  [17] 12.44992 12.49347 12.53593 12.57731 12.61765 12.65697 12.69505 12.73168
##  [25] 12.76692 12.80086 12.83355 12.86507 12.89549 12.92486 12.95327 12.98078
##  [33] 13.00745 13.03336 13.05857 13.08316 13.10588 13.12567 13.14284 13.15774
##  [41] 13.17068 13.18198 13.19199 13.20101 13.20939 13.21744 13.22549 13.23387
##  [49] 13.24291 13.25293 13.26269 13.27085 13.27753 13.28287 13.28701 13.29008
##  [57] 13.29223 13.29358 13.29427 13.29444 13.29422 13.29376 13.29318 13.29263
##  [65] 13.29379 13.29787 13.30431 13.31253 13.32195 13.33201 13.34213 13.35173
##  [73] 13.36025 13.36711 13.37173 13.37355 13.37199 13.36648 13.35794 13.34780
##  [81] 13.33620 13.32333 13.30934 13.29440 13.27868 13.26233 13.24552 13.22842
##  [89] 13.21119 13.19399 13.17699 13.16036 13.13857 13.10707 13.06746 13.02131
##  [97] 12.97025 12.91585 12.85973 12.80346 12.74866 12.69692 12.64982 12.60898
## [105] 12.57598 12.55243 12.53285 12.51113 12.48783 12.46354 12.43885 12.41434
## [113] 12.39059 12.36818 12.34769 12.32972 12.31484 12.30363 12.29668 12.29458
## [121] 12.30314 12.32636 12.36207 12.40813 12.46237 12.52263 12.58674 12.65256
## [129] 12.71791 12.78064 12.83858 12.88958 12.93148 12.96212 12.98361 13.00002
## [137] 13.01210 13.02059 13.02623 13.02977 13.03195 13.03353 13.03524 13.03782
## [145] 13.04203 13.04861 13.05830 13.06846 13.07634 13.08257 13.08775 13.09249
## [153] 13.09741 13.10313 13.10851 13.11231 13.11491 13.11671 13.11809 13.11945
## [161] 13.12119 13.12277 13.12350 13.12351 13.12296 13.12199 13.12074 13.11937
## [169] 13.11800 13.11661 13.11512 13.11342 13.11143 13.10904 13.10618 13.10274
## [177] 13.09863
#assign fits to a vector
both_trenda <- fit_botha

#extract y min and max for each
limits_botha <- ggplot_build(extract_botha)$data
## `geom_smooth()` using formula 'y ~ x'
limits_botha <- as.data.frame(limits_botha)
both_ymina <- limits_botha$ymin
both_ymaxa <- limits_botha$ymax

#reassign dataframes (just to be safe)
work_botha <- wrfa_both

#fill in missing dates to smooth fits
work_botha <- work_botha %>% complete(date = seq(min(date), max(date), by = "1 day"))
date_vec_botha <- work_botha$date

#create a new smooth dataframe to layer
smooth_frame_botha <- data.frame(date_vec_botha, both_trenda, both_ymina, both_ymaxa)
#WRF A
#plot smooth frames
p_wrf_a <- plotly::plot_ly() %>%
  plotly::add_lines(x = ~date_vec_botha, y = ~both_trenda,
                    data = smooth_frame_botha,
                    hoverinfo = "text",
                    text = ~paste('</br> Date: ', date_vec_botha,
                                  '</br> Median Log Copies: ', round(both_trenda, digits = 2)),
                    line = list(color = '#1B9E77', size = 8, opacity = 0.65),
                    showlegend = FALSE) %>%
     layout(xaxis = list(range = c(mindate - 7, maxdate + 7))) %>% #buffer here
plotly::add_ribbons(x ~date_vec_botha, ymin = ~both_ymina, ymax = ~both_ymaxa,
                    showlegend = FALSE,
                    opacity = 0.25,
                    hoverinfo = "text",
                    text = ~paste('</br> Date: ', date_vec_botha, #leaving in case we want to change
                                  '</br> Max Log Copies: ', round(both_ymaxa, digits = 2),
                                  '</br> Min Log Copies: ', round(both_ymina, digits = 2)),
                    name = "",
                    fillcolor = '#1B9E77',
                    line = list(color = '#1B9E77')) %>%
                layout(yaxis = list(title = "Total Log SARS CoV-2 Copies", 
                                 showline = TRUE,
                                 automargin = TRUE)) %>%
                layout(xaxis = list(title = "Date")) %>%
                layout(title = "WRF A") %>%
    plotly::add_segments(x = as.Date("2020-06-24"), 
                                          xend = as.Date("2020-06-24"), 
                                          y = ~min(both_ymina), yend = ~max(both_ymaxa),
                                          opacity = 0.35,
                                          name = "Bars Repoen",
                                          hoverinfo = "text",
                                          text = "</br> Bars Reopen",
                                                 "</br> 2020-06-24",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
    plotly::add_segments(x = as.Date("2020-07-09"), 
                                          xend = as.Date("2020-07-09"), 
                                          y = ~min(both_ymina), yend = ~max(both_ymaxa),
                                          opacity = 0.35,
                                          name = "Mask Mandate",
                                          hoverinfo = "text",
                                          text = "</br> Mask Mandate",
                                                 "</br> 2020-07-09",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
    plotly::add_segments(x = as.Date("2020-08-20"), 
                                          xend = as.Date("2020-08-20"), 
                                          y = ~min(both_ymina), yend = ~max(both_ymaxa),
                                          opacity = 0.35,
                                          name = "</br> Classes Begin",
                                                 "</br> 2020-08-20",
                                          hoverinfo = "text",
                                          text = "Classes Begin",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
        plotly::add_segments(x = as.Date("2020-10-03"), 
                                          xend = as.Date("2020-10-03"), 
                                          y = ~min(both_ymina), yend = ~max(both_ymaxa),
                                          opacity = 0.35,
                                          name = "</br> First Home Football Game",
                                                 "</br> 2020-10-03",
                                          hoverinfo = "text",
                                          text = "First Home Football Game",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
  plotly::add_markers(x = ~date, y = ~log_total_copies_both,
                      data = wrfa_both,
                       hoverinfo = "text",
                       showlegend = FALSE,
                       text = ~paste('</br> Date: ', date, 
                                     '</br> Actual Log Copies: ', round(log_total_copies_both, digits = 2)),
                       marker = list(color = '#1B9E77', size = 6, opacity = 0.65))

p_wrf_a
save(p_wrf_a, file = "./plotly_objs/p_wrf_a.rda")
#**************************************WRF B PLOT**********************************************
#add trendlines 
#extract data from geom_smooth
#both extract
# *********************************span 0.6***********************************
#*****************Must always update the n = TOTAL NUMBER OF DAYS*************************
extract_bothb <- ggplot(wrfb_both, aes(x = date, y = log_total_copies_both)) + 
  stat_smooth(aes(outfit=fit_bothb<<-..y..), method = "loess", color = '#D95F02', 
              span = 0.6, n = 177)
## Warning: Ignoring unknown aesthetics: outfit
#look at the fits to align dates and total observations
#both
extract_bothb
## `geom_smooth()` using formula 'y ~ x'

fit_bothb
##   [1] 11.53462 11.57472 11.61502 11.65502 11.69423 11.73214 11.76827 11.80212
##   [9] 11.83427 11.86565 11.89628 11.92619 11.95540 11.98392 12.01177 12.03898
##  [17] 12.06556 12.09154 12.11693 12.14176 12.16605 12.18981 12.21281 12.23487
##  [25] 12.25604 12.27642 12.29607 12.31508 12.33352 12.35146 12.36900 12.38619
##  [33] 12.40313 12.41988 12.43653 12.45315 12.46879 12.48261 12.49484 12.50572
##  [41] 12.51548 12.52434 12.53254 12.54031 12.54788 12.55548 12.56335 12.57171
##  [49] 12.58080 12.59085 12.59744 12.59679 12.59009 12.57852 12.56327 12.54552
##  [57] 12.52646 12.50727 12.48915 12.47326 12.46081 12.45298 12.45095 12.45590
##  [65] 12.47024 12.49446 12.52690 12.56590 12.60980 12.65694 12.70564 12.75427
##  [73] 12.80114 12.84459 12.88298 12.91463 12.93788 12.95107 12.96254 12.98092
##  [81] 13.00494 13.03335 13.06490 13.09833 13.13239 13.16583 13.19739 13.22582
##  [89] 13.24986 13.26826 13.27976 13.28312 13.27497 13.25408 13.22237 13.18178
##  [97] 13.13424 13.08167 13.02601 12.96919 12.91313 12.85977 12.81104 12.76886
## [105] 12.73517 12.71189 12.69074 12.66290 12.62954 12.59182 12.55093 12.50801
## [113] 12.46425 12.42080 12.37883 12.33952 12.30403 12.27352 12.24916 12.23212
## [121] 12.22113 12.21395 12.21031 12.20997 12.21265 12.21809 12.22603 12.23621
## [129] 12.24836 12.26223 12.27754 12.29405 12.31148 12.32957 12.35098 12.37756
## [137] 12.40781 12.44024 12.47336 12.50568 12.53570 12.56195 12.58706 12.61421
## [145] 12.64270 12.67182 12.70086 12.72913 12.75592 12.78202 12.80863 12.83562
## [153] 12.86289 12.89034 12.91787 12.94535 12.97285 13.00050 13.02834 13.05641
## [161] 13.08476 13.11341 13.14240 13.17171 13.20128 13.23111 13.26121 13.29159
## [169] 13.32225 13.35319 13.38446 13.41608 13.44803 13.48028 13.51282 13.54562
## [177] 13.57865
#assign fits to a vector
both_trendb <- fit_bothb

#extract y min and max for each
limits_bothb <- ggplot_build(extract_bothb)$data
## `geom_smooth()` using formula 'y ~ x'
limits_bothb <- as.data.frame(limits_bothb)
both_yminb <- limits_bothb$ymin
both_ymaxb <- limits_bothb$ymax

#reassign dataframes (just to be safe)
work_bothb <- wrfb_both

#fill in missing dates to smooth fits
work_bothb <- work_bothb %>% complete(date = seq(min(date), max(date), by = "1 day"))
date_vec_bothb <- work_bothb$date

#create a new smooth dataframe to layer
smooth_frame_bothb <- data.frame(date_vec_bothb, both_trendb, both_yminb, both_ymaxb)
#WRF B
#plot smooth frames
p_wrf_b <- plotly::plot_ly() %>%
  plotly::add_lines(x = ~date_vec_bothb, y = ~both_trendb,
                    data = smooth_frame_bothb,
                    hoverinfo = "text",
                    text = ~paste('</br> Date: ', date_vec_bothb,
                                  '</br> Median Log Copies: ', round(both_trendb, digits = 2)),
                    line = list(color = '#D95F02', size = 8, opacity = 0.65),
                    showlegend = FALSE) %>%
     layout(xaxis = list(range = c(mindate - 7, maxdate + 7))) %>% #buffer here
plotly::add_ribbons(x ~date_vec_bothb, ymin = ~both_yminb, ymax = ~both_ymaxb,
                    showlegend = FALSE,
                    opacity = 0.25,
                    hoverinfo = "text",
                    text = ~paste('</br> Date: ', date_vec_bothb, #leaving in case we want to change
                                  '</br> Max Log Copies: ', round(both_ymaxb, digits = 2),
                                  '</br> Min Log Copies: ', round(both_yminb, digits = 2)),
                    name = "",
                    fillcolor = '#D95F02',
                    line = list(color = '#D95F02')) %>%
                layout(yaxis = list(title = "Total Log SARS CoV-2 Copies", 
                                 showline = TRUE,
                                 automargin = TRUE)) %>%
                layout(xaxis = list(title = "Date")) %>%
                layout(title = "WRF B") %>%
    plotly::add_segments(x = as.Date("2020-06-24"), 
                                          xend = as.Date("2020-06-24"), 
                                          y = ~min(both_yminb), yend = ~max(both_ymaxb),
                                          opacity = 0.35,
                                          name = "Bars Repoen",
                                          hoverinfo = "text",
                                          text = "</br> Bars Reopen",
                                                 "</br> 2020-06-24",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
    plotly::add_segments(x = as.Date("2020-07-09"), 
                                          xend = as.Date("2020-07-09"), 
                                          y = ~min(both_yminb), yend = ~max(both_ymaxb),
                                          opacity = 0.35,
                                          name = "Mask Mandate",
                                          hoverinfo = "text",
                                          text = "</br> Mask Mandate",
                                                 "</br> 2020-07-09",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
    plotly::add_segments(x = as.Date("2020-08-20"), 
                                          xend = as.Date("2020-08-20"), 
                                          y = ~min(both_yminb), yend = ~max(both_ymaxb),
                                          opacity = 0.35,
                                          name = "</br> Classes Begin",
                                                 "</br> 2020-08-20",
                                          hoverinfo = "text",
                                          text = "Classes Begin",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
        plotly::add_segments(x = as.Date("2020-10-03"), 
                                          xend = as.Date("2020-10-03"), 
                                          y = ~min(both_yminb), yend = ~max(both_ymaxb),
                                          opacity = 0.35,
                                          name = "</br> First Home Football Game",
                                                 "</br> 2020-10-03",
                                          hoverinfo = "text",
                                          text = "First Home Football Game",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
  plotly::add_markers(x = ~date, y = ~log_total_copies_both,
                      data = wrfb_both,
                       hoverinfo = "text",
                       showlegend = FALSE,
                       text = ~paste('</br> Date: ', date, 
                                     '</br> Actual Log Copies: ', round(log_total_copies_both, digits = 2)),
                       marker = list(color = '#D95F02', size = 6, opacity = 0.65))

p_wrf_b
save(p_wrf_b, file = "./plotly_objs/p_wrf_b.rda")

#**************************************WRF C PLOT********************************************** #add trendlines #extract data from geom_smooth # *********************************span 0.6*********************************** #*****************Must always update the n = TOTAL NUMBER OF DAYS*************************

extract_bothc <- ggplot(wrfc_both, aes(x = date, y = log_total_copies_both)) + 
  stat_smooth(aes(outfit=fit_bothc<<-..y..), method = "loess", color = '#E7298A', 
              span = 0.6, n = 163)
## Warning: Ignoring unknown aesthetics: outfit
#look at the fits to align dates and total observations
#both
extract_bothc
## `geom_smooth()` using formula 'y ~ x'

fit_bothc
##   [1] 11.30721 11.35667 11.40495 11.45218 11.49849 11.54402 11.58891 11.63330
##   [9] 11.67709 11.72009 11.76229 11.80367 11.84421 11.88390 11.92272 11.96065
##  [17] 11.99767 12.03377 12.06894 12.10315 12.13639 12.16864 12.19988 12.23010
##  [25] 12.25928 12.28741 12.31446 12.34042 12.36527 12.38909 12.41192 12.43377
##  [33] 12.45462 12.47447 12.49330 12.51110 12.52787 12.54359 12.55825 12.57185
##  [41] 12.58436 12.59579 12.60613 12.61532 12.62338 12.63034 12.63626 12.64117
##  [49] 12.64512 12.64816 12.65032 12.65166 12.65222 12.65203 12.65116 12.64963
##  [57] 12.64751 12.64694 12.64962 12.65483 12.66187 12.67004 12.67863 12.68693
##  [65] 12.69424 12.69986 12.70308 12.70320 12.69951 12.69131 12.67789 12.65641
##  [73] 12.62543 12.58630 12.54043 12.48917 12.43390 12.37601 12.31687 12.25784
##  [81] 12.20032 12.14568 12.09529 12.05053 12.01278 11.97698 11.93751 11.89489
##  [89] 11.84963 11.80224 11.75326 11.70319 11.65255 11.60185 11.55162 11.50236
##  [97] 11.45461 11.40886 11.36565 11.32548 11.28888 11.25635 11.22842 11.20561
## [105] 11.18842 11.17738 11.17252 11.17316 11.17877 11.18881 11.20274 11.22002
## [113] 11.24012 11.26250 11.28661 11.31193 11.33792 11.36403 11.38973 11.41449
## [121] 11.44314 11.47961 11.52203 11.56850 11.61714 11.66605 11.71335 11.75715
## [129] 11.80011 11.84568 11.89316 11.94186 11.99106 12.04008 12.08821 12.13474
## [137] 12.17899 12.22024 12.25780 12.29097 12.32167 12.35205 12.38178 12.41050
## [145] 12.43787 12.46354 12.48717 12.50929 12.53054 12.55074 12.56973 12.58733
## [153] 12.60338 12.61769 12.63026 12.64120 12.65056 12.65840 12.66475 12.66966
## [161] 12.67317 12.67533 12.67619
#assign fits to a vector
both_trendc <- fit_bothc

#extract y min and max for each
limits_bothc <- ggplot_build(extract_bothc)$data
## `geom_smooth()` using formula 'y ~ x'
limits_bothc <- as.data.frame(limits_bothc)
both_yminc <- limits_bothc$ymin
both_ymaxc <- limits_bothc$ymax

#reassign dataframes (just to be safe)
work_bothc <- wrfc_both

#fill in missing dates to smooth fits
work_bothc <- work_bothc %>% complete(date = seq(min(date), max(date), by = "1 day"))
date_vec_bothc <- work_bothc$date

#create a new smooth dataframe to layer
smooth_frame_bothc <- data.frame(date_vec_bothc, both_trendc, both_yminc, both_ymaxc)
#WRF C
#plot smooth frames
p_wrf_c <- plotly::plot_ly() %>%
  plotly::add_lines(x = ~date_vec_bothc, y = ~both_trendc,
                    data = smooth_frame_bothc,
                    hoverinfo = "text",
                    text = ~paste('</br> Date: ', date_vec_bothc,
                                  '</br> Median Log Copies: ', round(both_trendc, digits = 2)),
                    line = list(color = '#E7298A', size = 8, opacity = 0.65),
                    showlegend = FALSE) %>%
     layout(xaxis = list(range = c(mindate - 7, maxdate + 7))) %>% #buffer here
plotly::add_ribbons(x ~date_vec_bothc, ymin = ~both_yminc, ymax = ~both_ymaxc,
                    showlegend = FALSE,
                    opacity = 0.25,
                    hoverinfo = "text",
                    text = ~paste('</br> Date: ', date_vec_bothc, #leaving in case we want to change
                                  '</br> Max Log Copies: ', round(both_ymaxc, digits = 2),
                                  '</br> Min Log Copies: ', round(both_yminc, digits = 2)),
                    name = "",
                    fillcolor = '#E7298A',
                    line = list(color = '#E7298A')) %>%
                layout(yaxis = list(title = "Total Log SARS CoV-2 Copies", 
                                 showline = TRUE,
                                 automargin = TRUE)) %>%
                layout(xaxis = list(title = "Date")) %>%
                layout(title = "WRF C") %>%
    plotly::add_segments(x = as.Date("2020-06-24"), 
                                          xend = as.Date("2020-06-24"), 
                                          y = ~min(both_yminc), yend = ~max(both_ymaxc),
                                          opacity = 0.35,
                                          name = "Bars Repoen",
                                          hoverinfo = "text",
                                          text = "</br> Bars Reopen",
                                                 "</br> 2020-06-24",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
    plotly::add_segments(x = as.Date("2020-07-09"), 
                                          xend = as.Date("2020-07-09"), 
                                          y = ~min(both_yminc), yend = ~max(both_ymaxc),
                                          opacity = 0.35,
                                          name = "Mask Mandate",
                                          hoverinfo = "text",
                                          text = "</br> Mask Mandate",
                                                 "</br> 2020-07-09",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
    plotly::add_segments(x = as.Date("2020-08-20"), 
                                          xend = as.Date("2020-08-20"), 
                                          y = ~min(both_yminc), yend = ~max(both_ymaxc),
                                          opacity = 0.35,
                                          name = "</br> Classes Begin",
                                                 "</br> 2020-08-20",
                                          hoverinfo = "text",
                                          text = "Classes Begin",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
        plotly::add_segments(x = as.Date("2020-10-03"), 
                                          xend = as.Date("2020-10-03"), 
                                          y = ~min(both_yminc), yend = ~max(both_ymaxc),
                                          opacity = 0.35,
                                          name = "</br> First Home Football Game",
                                                 "</br> 2020-10-03",
                                          hoverinfo = "text",
                                          text = "First Home Football Game",
                                          showlegend = FALSE,
                                          line = list(color = "black", dash = "dash")) %>%
  plotly::add_markers(x = ~date, y = ~log_total_copies_both,
                      data = wrfc_both,
                       hoverinfo = "text",
                       showlegend = FALSE,
                       text = ~paste('</br> Date: ', date, 
                                     '</br> Actual Log Copies: ', round(log_total_copies_both, digits = 2)),
                       marker = list(color = '#E7298A', size = 6, opacity = 0.65))

p_wrf_c
save(p_wrf_c, file = "./plotly_objs/p_wrf_c.rda")
save(wrfa_both, file = "./plotly_objs/wrfa_both.rda")
save(wrfb_both, file = "./plotly_objs/wrfb_both.rda")
save(wrfc_both, file = "./plotly_objs/wrfc_both.rda")
save(date_vec_botha, file = "./plotly_objs/date_vec_botha.rda")
save(date_vec_bothb, file = "./plotly_objs/date_vec_bothb.rda")
save(date_vec_bothc, file = "./plotly_objs/date_vec_bothc.rda")
save(both_ymina, file = "./plotly_objs/both_ymina.rda")
save(both_ymaxa, file = "./plotly_objs/both_ymaxa.rda")

save(both_yminb, file = "./plotly_objs/both_yminb.rda")
save(both_ymaxb, file = "./plotly_objs/both_ymaxb.rda")

save(both_yminc, file = "./plotly_objs/both_yminc.rda")
save(both_ymaxc, file = "./plotly_objs/both_ymaxc.rda")